{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "mpl.rcParams[\"lines.linewidth\"]=5\n",
    "mpl.rcParams[\"lines.linestyle\"]=\"--\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x16b1fd84748>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots()\n",
    "ax.plot([0,1,2,3],)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x16b1fd05948>]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "fig,ax=plt.subplots()\n",
    "ax.plot(np.array([0,1,2,3])*1.2,color=\"red\",lw=2,ls=\"--\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x16b20ea1848>]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots()\n",
    "ax.plot(np.array([0,1,2,3])+1)\n",
    "ax.plot(np.array([0,1,2,3])+2)\n",
    "ax.plot(np.array([0,1,2,3])+3)\n",
    "ax.plot(np.array([0,1,2,3])+4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x16b20f34fc8>]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from cycler import cycler\n",
    "mpl.rcParams['axes.prop_cycle'] = cycler(color=['r', 'g', 'b', 'y',\"k\"])\n",
    "fig,ax=plt.subplots()\n",
    "ax.plot(np.array([0,1,2,3])+1)\n",
    "ax.plot(np.array([0,1,2,3])+2)\n",
    "ax.plot(np.array([0,1,2,3])+3)\n",
    "ax.plot(np.array([0,1,2,3])+4)\n",
    "\n",
    "ax.plot(np.array([0,1,2,3])+5)\n",
    "ax.plot(np.array([0,1,2,3])+6)\n",
    "ax.plot(np.array([0,1,2,3])+7)\n",
    "ax.plot(np.array([0,1,2,3])+8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x16b20efbe88>]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots()\n",
    "ax.plot(np.array([0,1,2,3]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "with mpl.rc_context({'lines.linewidth': 1, 'lines.linestyle': '--'}):\n",
    "    fig,ax=plt.subplots()\n",
    "    ax.plot([0,1,2,3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x16b212e8248>]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots()\n",
    "ax.plot(np.array([0,1,2,3]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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